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Chinese Offensive Language Detection:Current Status and Future Directions

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arxiv 2403.18314 v3 pith:MWQ3CRRK submitted 2024-03-27 cs.CL cs.AI

classification cs.CLcs.AI
keywords languageoffensivechinesechallengecomplexcurrentdetectingdetection
verification ladder T0 review T1 audit T2 compute T3 formal
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Despite the considerable efforts being made to monitor and regulate user-generated content on social media platforms, the pervasiveness of offensive language, such as hate speech or cyberbullying, in the digital space remains a significant challenge. Given the importance of maintaining a civilized and respectful online environment, there is an urgent and growing need for automatic systems capable of detecting offensive speech in real time. However, developing effective systems for processing languages such as Chinese presents a significant challenge, owing to the language's complex and nuanced nature, which makes it difficult to process automatically. This paper provides a comprehensive overview of offensive language detection in Chinese, examining current benchmarks and approaches and highlighting specific models and tools for addressing the unique challenges of detecting offensive language in this complex language. The primary objective of this survey is to explore the existing techniques and identify potential avenues for further research that can address the cultural and linguistic complexities of Chinese.

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  1. Lost in Pronunciation: Detecting Chinese Offensive Language Disguised by Phonetic Cloaking Replacement

    cs.CL 2025-07 conditional novelty 6.0 of 10

    A new 500-post benchmark of naturally occurring phonetic cloaking shows LLMs detect such Chinese offensive language with F1 at most 0.672, and Pinyin-augmented prompting partially repairs the gap.

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